BIC.logLik               package:nlme               R Documentation

_B_I_C _o_f _a _l_o_g_L_i_k _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     This function calculates the Bayesian information criterion, also
     known as Schwarz's Bayesian criterion (SBC) for an object
     inheriting from class 'logLik', according to the formula 
     log-likelihood + npar*log(nobs), where npar represents the number
     of parameters  and nobs the number of  observations in the fitted
     model. When comparing fitted objects, the smaller the BIC, the
     better the fit.

_U_s_a_g_e:

     ## S3 method for class 'logLik':
     BIC(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'logLik', usually resulting
          from applying a 'logLik' method to a fitted model object.

     ...: some methods for this generic use optional arguments. None
          are used in this method.

_V_a_l_u_e:

     a numeric value with the corresponding BIC.

_A_u_t_h_o_r(_s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

_R_e_f_e_r_e_n_c_e_s:

     Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals
     of Statistics, 6, 461-464.

_S_e_e _A_l_s_o:

     'BIC', 'logLik', 'AIC'

_E_x_a_m_p_l_e_s:

     data(Orthodont)
     fm1 <- lm(distance ~ age, data = Orthodont) 
     BIC(logLik(fm1))

